Evidence map›Paper›PMID 32570016›Full record

ReviewDiabetes & metabolic syndrome

Application of cognitive Internet of Medical Things for COVID-19 pandemic.

Swati Swayamsiddha, Chandana Mohanty

Erratum issuedAbstract readReview
In one paragraph

Review in Diabetes & metabolic syndrome. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. The metaverse in medicine.European heart journal supplements : journal of the European Society of Cardiology · 2023
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  16. Advances in the Rapid Diagnostic of Viral Respiratory Tract Infections.Frontiers in cellular and infection microbiology · 2022
    Review
  17. Review
  18. Article
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  20. The Role of Emerging Technologies to Fight Against COVID-19 Pandemic: An Exploratory Review.Transactions of the Indian National Academy of Engineering : an international journal of engineering and technology · 2022
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Swati SwayamsiddhaSchool of Electronics Engineering, KIIT University, Bhubaneswar, Odisha, India.
Chandana MohantySchool of Applied Science, KIIT University, Bhubaneswar, Odisha, India. Electronic address: chandana.mohantyfbs@kiit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimIn the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management.

methodsAn extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms "COVID-19" and "Cognitive IoT" or "Corona virus" and "IoMT". The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas.

resultsThis review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified.

conclusionsCIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others.

Indexed as

CognitionBetacoronavirusCoronavirus InfectionsCOVID-19Delivery of Health CareHumansInternet of ThingsPandemicsPneumonia, ViralSARS-CoV-2TelemedicineCognitive Internet of Medical Things (CIoMT)CoronavirusCOVID-19Internet of Things (IoT)

Identifiers

PMID32570016
PMCPMC7287427

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.